Multipopulation genetic programming for forecasting crop pests

被引:0
|
作者
Tang, LJ [1 ]
Li, M [1 ]
Zhang, J [1 ]
机构
[1] Chinese Acad Sci, Hefei Inst Intelligent Machines, Hefei 230031, Anhui, Peoples R China
来源
PROCEEDINGS OF 2003 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS & SIGNAL PROCESSING, PROCEEDINGS, VOLS 1 AND 2 | 2003年
关键词
multipopulation; genetic programming; forecasting crop pests; migration;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This contribution attempts to study on forecasting crop pests with Multipopulation Genetic Programming (MGP). In our previous work, Standard Genetic Programming (SGP) evolves a single population, which often results in premature convergence. This paper concentrates on multipopulation evolution in order to maintain population diversity to avoid this. Comparison between single and multi population shows superiority of the latter. Study of migration interval and migration rate draws the conclusion that it is helpful to obtain optimal solutions that subpopulations keep communicating often and only a few of individuals migrate when communicating. All experiments are based on forecasting wheat stripe rust disease. MGP shows good prediction, which is hopeful to become an auxiliary method for forecasting crop pests.
引用
收藏
页码:554 / 557
页数:4
相关论文
共 50 条
  • [1] Study on forecasting of crop pests with genetic programming
    Tang, LJ
    Li, M
    Zhang, J
    7TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL II, PROCEEDINGS: COMPUTER SCIENCE AND ENGINEERING, 2003, : 239 - 243
  • [2] An empirical study of multipopulation genetic programming
    Francisco Fernández
    Marco Tomassini
    Leonardo Vanneschi
    Genetic Programming and Evolvable Machines, 2003, 4 (1) : 21 - 51
  • [3] Symbolic regression of crop pest forecasting using genetic programming
    Alhadidi, Basim
    Al-Afeef, Alaa
    Al-Hiary, Heba
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2012, 20 : 1332 - 1342
  • [4] Medical knowledge representation by means of multipopulation genetic programming: An application to burn diagnosing.
    de Vega, FF
    Roa, LM
    Tomassini, M
    Sanchez, JM
    PROCEEDINGS OF THE 22ND ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4, 2000, 22 : 619 - 622
  • [5] Time series forecasting with genetic programming
    Mario Graff
    Hugo Jair Escalante
    Fernando Ornelas-Tellez
    Eric S. Tellez
    Natural Computing, 2017, 16 : 165 - 174
  • [6] Time series forecasting with genetic programming
    Graff, Mario
    Jair Escalante, Hugo
    Ornelas-Tellez, Fernando
    Tellez, Eric S.
    NATURAL COMPUTING, 2017, 16 (01) : 165 - 174
  • [7] Genetic Programming for storm surge forecasting
    Nguyen Thi Hien
    Cao Truong Tran
    Xuan Hoai Nguyen
    Kim, Sooyoul
    Vu Dinh Phai
    Nguyen Ba Thuy
    Ngo Van Manh
    OCEAN ENGINEERING, 2020, 215
  • [8] Collective Intelligence of Genetic Programming for Macroeconomic Forecasting
    Duda, Jerzy
    Szydlo, Stanislaw
    COMPUTATIONAL COLLECTIVE INTELLIGENCE: TECHNOLOGIES AND APPLICATIONS, PT II: THIRD INTERNATIONAL CONFERENCE, ICCCI 2011, 2011, 6923 : 445 - +
  • [9] Drafting Force Forecasting Using Genetic Programming
    Nibikora, Ildephonse
    Wang, Jun
    SILK: INHERITANCE AND INNOVATION - MODERN SILK ROAD, 2011, 175-176 : 355 - 359
  • [10] Genetic programming for photovoltaic plant output forecasting
    Russo, M.
    Leotta, G.
    Pugliatti, P. M.
    Gigliucci, G.
    SOLAR ENERGY, 2014, 105 : 264 - 273